OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 7 million. The library is used extensively in companies, research groups and by governmental bodies. ..

References in zbMATH (referenced in 41 articles )

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  1. Žbontar, Jure; Lecun, Yann: Stereo matching by training a convolutional neural network to compare image patches (2016)
  2. Gallego, Guillermo; Yezzi, Anthony: A compact formula for the derivative of a 3-D rotation in exponential coordinates (2015)
  3. Goodfellow, Ian J.; Erhan, Dumitru; Luc Carrier, Pierre; Courville, Aaron; Mirza, Mehdi; Hamner, Ben; Cukierski, Will; Tang, Yichuan; Thaler, David; Lee, Dong-Hyun; Zhou, Yingbo; Ramaiah, Chetan; Feng, Fangxiang; Li, Ruifan; Wang, Xiaojie; Athanasakis, Dimitris; Shawe-Taylor, John; Milakov, Maxim; Park, John; Ionescu, Radu; Popescu, Marius; Grozea, Cristian; Bergstra, James; Xie, Jingjing; Romaszko, Lukasz; Xu, Bing; Chuang, Zhang; Bengio, Yoshua: Challenges in representation learning: A report on three machine learning contests (2015)
  4. Kryvonos, Iu.G.; Krak, Iu.V.; Barmak, O.V.; Ternov, A.S.; Kuznetsov, V.O.: Information technology for the analysis of mimic expressions of human emotional states (2015)
  5. Song, Dan; Wang, Dongming; Chen, Xiaoyu: Discovering geometric theorems from scanned and photographed images of diagrams (2015)
  6. Drevelle, Vincent; Nicola, Jeremy: VIBes: a visualizer for intervals and boxes (2014)
  7. Gaidon, Adrien; Harchaoui, Zaid; Schmid, Cordelia: Activity representation with motion hierarchies (2014)
  8. Karpov, A.A.: An automatic multimodal speech recognition system with audio and video information (2014)
  9. Morshidi, Malik; Tjahjadi, Tardi: Gravity optimised particle filter for hand tracking (2014)
  10. Ronda, José I.; Valdés, Antonio; Gallego, Guillermo: Autocalibration with the minimum number of cameras with known pixel shape (2014)
  11. Zagoris, Konstantinos; Pratikakis, Ioannis; Antonacopoulos, Apostolos; Gatos, Basilis; Papamarkos, Nikos: Distinction between handwritten and machine-printed text based on the bag of visual words model (2014)
  12. Bucur, Laurentiu; Florea, Adina; Chera, Catalin: A KBRL inference metaheuristic with applications (2013)
  13. Bukhari, Faisal; Dailey, Matthew N.: Automatic radial distortion estimation from a single image (2013)
  14. F.F.Belussi, Luiz; S.T.Hirata, Nina: Fast component-based QR code detection in arbitrarily acquired images (2013)
  15. Liu, Minxiang; Wang, Yuhao; Leung, Henry; Yu, Jiangnan: A novel feature-level data fusion method for indoor autonomous localization (2013)
  16. Malleson, Charles; Collomosse, John: Virtual volumetric graphics on commodity displays using 3D viewer tracking (2013)
  17. Manfredi, L.; Assaf, T.; Mintchev, S.; Marrazza, S.; Capantini, L.; Orofino, S.; Ascari, L.; Grillner, S.; Wallén, P.; Ekeberg, Ö.; Stefanini, C.; Dario, P.: A bioinspired autonomous swimming robot as a tool for studying goal-directed locomotion (2013)
  18. Simpkins, Jonathan D.; Stevenson, Robert L.: An introduction to super-resolution imaging (2013)
  19. Wang, Nan; Ai, Hai-Zhou; Tang, Feng: Who blocks who: simultaneous segmentation of occluded objects (2013)
  20. Abramov, Alexey: Compression of visual data into symbol-like descriptors in terms of a cognitive real-time vision system (2012)

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